Community Interaction and Conflict on the Web
Srijan Kumar, William L. Hamilton, Jure Leskovec, Dan Jurafsky

TL;DR
This study analyzes intercommunity conflicts on Reddit, revealing conflict initiation patterns, long-term negative effects, and proposing predictive models and mitigation strategies to foster healthier online communities.
Contribution
It provides a comprehensive analysis of community conflicts, identifies key conflict initiators, and introduces a novel LSTM model for early conflict prediction and mitigation.
Findings
Less than 1% of communities start 74% of conflicts.
Conflicts lead to echo chambers and reduced activity in targeted communities.
A novel LSTM model accurately predicts conflicts using graph, user, community, and text features.
Abstract
Users organize themselves into communities on web platforms. These communities can interact with one another, often leading to conflicts and toxic interactions. However, little is known about the mechanisms of interactions between communities and how they impact users. Here we study intercommunity interactions across 36,000 communities on Reddit, examining cases where users of one community are mobilized by negative sentiment to comment in another community. We show that such conflicts tend to be initiated by a handful of communities---less than 1% of communities start 74% of conflicts. While conflicts tend to be initiated by highly active community members, they are carried out by significantly less active members. We find that conflicts are marked by formation of echo chambers, where users primarily talk to other users from their own community. In the long-term, conflicts have…
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Taxonomy
MethodsSigmoid Activation · Tanh Activation · Long Short-Term Memory
